CN103063603B - Machine-fried Longjing tea moisture content on-line detection device - Google Patents
Machine-fried Longjing tea moisture content on-line detection device Download PDFInfo
- Publication number
- CN103063603B CN103063603B CN201210571483.1A CN201210571483A CN103063603B CN 103063603 B CN103063603 B CN 103063603B CN 201210571483 A CN201210571483 A CN 201210571483A CN 103063603 B CN103063603 B CN 103063603B
- Authority
- CN
- China
- Prior art keywords
- light source
- light
- machine
- fried
- longjing tea
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention provides a machine-fried Longjing tea moisture content on-line detection device based on spectral characteristic parameters. At first, a sampling scheme is determined by utilizing a uniform design method, full-wave band spectrum of the machine-fried Longjing tea is achieved through a high spectrograph to be preprocessed and analyzed. Sensitive spectral band is determined and the spectral feature parameters are achieved through a relative analysis for the machine-fried machine Longjing tea moisture content, so that the machine-fried Longjing tea moisture content is predicted by building an inversion model through a small sample nonequilibrium theory and an ant colony algorithm. The machine-fried Longjing tea moisture content on-line detection device can achieve the machine-fried Longjing tea moisture content online real-time detection and can be used in a full-automatic tea processing device system to improve the production efficiency.
Description
Technical field
The present invention relates to the detection technique based on infrared spectrum, especially can realize the online measuring technique to Measuring Moisture Content of Tea content, Longjing tea moisture on-line measuring device fried by the machine that is specifically related to.
Background technology
Measuring Moisture Content of Tea on-line checkingi is that most important link in Tea Production process fried by machine.Tealeaves is a kind of agricultural product of drying.Bromatology theory is thought, absolutely dry food is directly exposed to air because of each constituents, is subject to the oxidation of oxygen in air.And when hydrone combines with hydrogen bond and food composition, during in unimolecular layer state, like coveing with layer protecting film at food surface, food is protected, and makes oxidation progress slow down.Much research shows, when the water cut in tealeaves is about 3% time, tea component and hydrone almost in monomolecular relation, play good buffer action to oxygen molecule in lipid and air, stop the oxidation deterioration of lipid.But after moisture exceedes some, the large change of situation, not only can not play diaphragm effect, play solvent action on the contrary.The characteristic of solvent makes solutes accumulation, aggravation reaction.When Measuring Moisture Content of Tea content is more than 6%, or ambient atmosphere relative humidity higher than more than 6O% time, the chemical change in tealeaves can be made very fierce, and as chlorophyllous sex change, decomposition, color and luster browning deepens; The taste compound such as Tea Polyphenols, amino acid reduces rapidly; The aromatic substance such as dimethyl sulfide, phenylethyl alcohol of composition newly picked and processed tea leaves fragrance falls sharply, and rolls up the disadvantageous volatile ingredient of fragrance, causes tea leaf quality to become bad.Therefore, the water cut becoming to sample tea must control below 6%, exceedes this limit and then wants complex fire to dry, could preserve.
What mostly adopt in prior art is Oven Method and fast tester for water content method, and its ultimate principle is all by type of heating, rapid draing sample, obtains the content of Measuring Moisture Content of Tea by the change of example weight before and after measuring.The method measuring process is complicated, generally needs time a few minutes, therefore can not meet the requirement that Measuring Moisture Content of Tea detects in real time.Therefore be necessary design a kind of easy, quick, without damage method, to detect the moisture in tealeaves in real time.
Summary of the invention
For above-mentioned the deficiencies in the prior art part, the object of this invention is to provide a kind of structure simple, fast, be easy to control, the machine of the feature based spectrum parameter of dependable performance fries Longjing tea moisture on-line pick-up unit.
According to an aspect of the present invention, provide a kind of machine to fry Longjing tea moisture on-line measuring device, comprise light source, spectroscope, photodetector, filtering and amplifying circuit, A/D convertor circuit, single-chip microcomputer, display, wherein:
The light that described light source sends is divided into first via light and the second road light by described spectroscope, and wherein, described first via light is reference light source, and described second road light is irradiate the incident light to Tea Samples;
Described photodetector is used for the spectral signal generating described reference light source according to the described reference light source collected, and generates the spectral signal of described reflected light according to the reflected light of the described incident light irradiation Tea Samples acquisition collected;
Described A/D convertor circuit is used for converting the spectral signal of the described reference light source after described filtering and amplifying circuit process to reference light source spectral digital signal, converts the spectral signal of the described reflected light after described filtering and amplifying circuit process to reflected light spectral digital signal;
Described single-chip microcomputer is used for according to described reference light source spectral digital signal and reflected light spectral digital signal, draw the reflectivity of sensitive band spectrum, the Nonlinear Prediction Models then reflectivity of described sensitive band spectrum being substituted into machine stir-fry Longjing tea moisture and characteristic spectrum reflectivity draws the moisture of tealeaves;
Described display is for showing the moisture of described tealeaves.
Preferably, also comprise the first optical filter and the second optical filter, wherein, described light source comprises the first light source, secondary light source, the light that described first light source sends arrives described spectroscope through described first optical filter, and the light that described secondary light source sends arrives described spectroscope through described second optical filter.
Preferably, described sensitive band spectrum is the spectrum of 350-2500nm wavelength coverage.
Preferably, described sensitive band spectrum is the spectrum of these two wave bands of 708nm and 1432nm.
Preferably, the Nonlinear Prediction Models of Longjing tea moisture and characteristic spectrum reflectivity fried by described machine, be specially: the reflectivity utilizing sensitive band spectrum, use inversed-Gaussian model fit-spectra curve, ask for Red-edge parameter and absorb the degree of depth two characteristic parameters, adopt small sample non-statistical theory and independent component analysis method, the Nonlinear Prediction Models obtained.
Preferably, described light source is infrarede emitting diode.
Preferably, the light that light source sends by described spectroscope is divided into first via light and the second road light according to the ratio of 1:1.
Below the details of content of the present invention is made a more detailed description.
1) acquisition of all band tealeaves spectrum samples
Utilize EO-1 hyperion instrument to obtain machine and fry spectroscopic data in the different time of picking (spring tea and autumn tea) of Longjing tea, different moisture content (65%, 50%, 45%, 40%, 35%, 30%, 20% and 15%), the fresh leaf of various position leaves (in leaf and blade tip) and cured leaf 350-2500nm full band range, utilize the sampling plan that Uniform ity Design Method determination Three factors is multilevel, notice that each sample spectrum is limited in 10s to prevent leaf oxidation sweep time.
2) determination of sensitivity spectrum wave band
The spectrum of moisture in tealeaves to some specific band has obvious absorption effect, and this wave band is called the sensitive features spectrum of Measuring Moisture Content of Tea.As shown in Figure 1, spectrometer is utilized to obtain the reflectance spectrum of tealeaves in 350-2500nm wavelength coverage, by the data processing software of independent development to the tea fresh leaves of 8 different in moisture content, each 60 groups of smoothing pre-service of data, then statistical analysis technique and variance analysis method is adopted, filter out two sensitive bands reaching 0.86 with Measuring Moisture Content of Tea coefficient R, namely these two wave bands of red spectral band 708nm and near-infrared band 1432nm are as characteristic spectrum, and set up the polynary high order regression equation of sensitive band reflectivity and moisture.
3) moisture and spectral signature nonlinearity in parameters forecast model
Using red spectral band 708nm and near-infrared band 1432nm as analytic target, utilize Gauss red limit model (IG model) to simulate continuous spectrum curve, then ask and calculate Red-edge parameter and spectral absorption depth parameter and do correlation analysis, finally adopt small sample non-statistical theory and ant group algorithm to carry out data modeling, machine of setting up fries Longjing tea moisture and spectral signature nonlinearity in parameters forecast model.
4) mensuration of Longjing tea moisture fried by machine
For tealeaves to be detected, as shown in Figure 3, first use two groups of infrarede emitting diodes A, B, be divided into two-way respectively by after different optical filters through spectroscope in the ratio of 1:1, a road is reference light source A, B, and another road is incident light A, B.Reference light source A, B through photodetector A, B, convert analog electrical signal to spectral signal respectively, analog electrical signal after amplification filtering process again through A D convert digital signal to and be input to single-chip microcomputer inside.Incident light A, B irradiate tealeaves surface, obtain reflected light A, B, reflected light A, B are respectively through photodetector C, D, spectral signal is converted to analog electrical signal, analog electrical signal after amplification filtering process again through A D convert digital signal to and be input to single-chip microcomputer inside, together process with the data after reference light source process, draw the reflectivity of characteristic spectrum, the Nonlinear Prediction Models substituting into machine stir-fry Longjing tea moisture and characteristic spectrum reflectivity again draws and the moisture of tealeaves shows finally by LED.
Accompanying drawing explanation
By reading the detailed description done non-limiting example with reference to the following drawings, other features, objects and advantages of the present invention will become more obvious:
Fig. 1 is the reflected light spectrogram that Longjing tea fried by machine, and the tea fresh leaves curve of spectrum of 8 different in moisture content is shown;
Fig. 2 is that the tea fresh leaves of 8 different in moisture content is checked at the F of different wave length relative reflectance;
Fig. 3 is the schematic diagram that Longjing tea moisture online test method fried by machine;
Fig. 4 is the general assembly drawing that Longjing tea moisture on-line measuring device fried by machine;
Fig. 5 is the structural representation of photoelectric conversion interface;
Fig. 6 is down the red marginal ray spectrum of Gauss curve fitting;
Fig. 7 is matching differential smoothing curve;
Fig. 8 absorbs degree of depth estimation moisture.
In figure:
1 is spectroscope,
2 is light source jack,
3 is blank lay down location,
4 is sample tray lay down location,
5 is photoelectric sensor interface,
6 is shell,
7 is hydropneumatic O-ring seal.
Embodiment
Below in conjunction with specific embodiment, the present invention is described in detail.Following examples will contribute to those skilled in the art and understand the present invention further, but not limit the present invention in any form.It should be pointed out that to those skilled in the art, without departing from the inventive concept of the premise, some distortion and improvement can also be made.These all belong to protection scope of the present invention.
Fry Longjing tea moisture on-line checkingi object for reaching a kind of machine that is easy, quick, nothing damage, implementation process of the present invention is as follows:
1) acquisition of all band tealeaves spectrum samples
Utilize EO-1 hyperion instrument to obtain machine and fry spectroscopic data in the different time of picking (spring tea and autumn tea) of Longjing tea, different moisture content (65%, 50%, 45%, 40%, 35%, 30%, 20% and 15%), the fresh leaf of various position leaves (in leaf and blade tip) and cured leaf 350-2500nm full band range, utilize the sampling plan that Uniform ity Design Method determination Three factors is multilevel, notice that each sample spectrum is limited in 10s to prevent leaf oxidation sweep time.
2) sensitivity spectrum is selected
The spectrum of moisture in tealeaves to some specific band has obvious absorption effect, and this wave band is called the sensitive features spectrum of Measuring Moisture Content of Tea.As shown in Figure 1, spectrometer is utilized to obtain the reflectance spectrum of tealeaves in 350-2500nm wavelength coverage, by the data processing software of independent development to the tea fresh leaves of 8 different in moisture content, each 60 groups of smoothing pre-service of data, then statistical analysis technique and variance analysis method is adopted, filter out two sensitive bands reaching 0.86 with Measuring Moisture Content of Tea coefficient R, namely these two wave bands of red spectral band 708nm and near-infrared band 1432nm are as characteristic spectrum, and set up the polynary high order regression equation of sensitive band reflectivity and moisture.
3) Nonlinear Prediction Models of moisture and characteristic spectrum reflectivity
Using red spectral band 708nm and near-infrared band 1432nm as analytic target, utilize Gauss red limit model (IG model) to simulate continuous spectrum curve, then ask and calculate Red-edge parameter and the spectral absorption degree of depth (area) parameter and do correlation analysis, finally adopt small sample non-statistical theory and ant group algorithm to carry out data modeling, machine of setting up fries Longjing tea moisture and spectral signature nonlinearity in parameters forecast model.
4) mensuration of Longjing tea moisture fried by machine
Selective radiation energy major part concentrates on the light source in the wavelength band of characteristic absorption spectrum to be analyzed, selected infrarede emitting diode.Optical filter is selected to interfere narrow band pass filter, and to the wave band that will pass through, optical energy loss is little, and has good thermal stability.Semi-conductor photodetector selected by photodetector, and selectivity is good, highly sensitive, zero point stability.
For tealeaves to be detected, as shown in Figure 3, first use two groups of infrarede emitting diodes A, B, be divided into two-way respectively by after different optical filters through spectroscope in the ratio of 1:1, a road is reference light source A, B, and another road is incident light A, B.Reference light source A, B through photodetector A, B, convert analog electrical signal to spectral signal respectively, analog electrical signal after amplification filtering process again through A D convert digital signal to and be input to single-chip microcomputer inside.Incident light A, B irradiate tealeaves surface, obtain reflected light A, B, reflected light A, B are respectively through photodetector, spectral signal is converted to analog electrical signal, analog electrical signal after amplification filtering process again through A D convert digital signal to and be input to single-chip microcomputer inside, together process with the data after reference light source process, draw the reflectivity of characteristic spectrum, the Nonlinear Prediction Models substituting into machine stir-fry Longjing tea moisture and characteristic spectrum reflectivity again draws and the moisture of tealeaves shows finally by LED.
In a specific embodiment of the present invention, as shown in Figure 4, the preferably circular array arrangement of described light source jack 2, described light source is installed, blank lay down location 3 and sample tray lay down location 4 is provided with in the bottom of shell, tealeaves is positioned in sample tray, the reflected light that the light that described light source sends reflects through blank is as described reference light source, described light source is divided into two groups of infrarede emitting diodes, one group of infrarede emitting diode sends the light of 708nm wave band after the first optical filter, another group infrarede emitting diode sends the light of 1432nm wave band after the second optical filter, correspondingly, the quantity of described photoelectric sensor interface is preferably 4, be respectively used to the reference light source receiving 708nm wave band, the reflected light of 708nm wave band, the reference light source of 1432nm wave band, the reflected light of 1432nm wave band.
In further detail, utilize the present invention can realize a kind of machine and fry Longjing tea moisture online test method.
Described machine is fried Longjing tea moisture online test method and is comprised the steps:
Step one: the light sent by light source is divided into first via light and the second road light, wherein, described first via light is reference light source, and described second road light is irradiate the incident light to Tea Samples; The light preferably sent by light source is divided into first via light and the second road light according to the ratio of 1:1.
Step 2: the spectral signal of described reference light source is converted to reference light source spectral digital signal, then stores described reference light source spectral digital signal; Gather the reflected light that described incident light irradiation Tea Samples obtains, then convert the spectral signal of described reflected light to reflected light spectral digital signal, store described reflected light spectral digital signal;
Step 3: according to described reference light source spectral digital signal and reflected light spectral digital signal, draw the reflectivity of sensitive band spectrum, then the Nonlinear Prediction Models reflectivity of described sensitive band spectrum being substituted into machine stir-fry Longjing tea moisture and characteristic spectrum reflectivity draws the moisture of tealeaves, and shows the moisture of described tealeaves.
Described sensitive band spectrum is the spectrum of 350-2500nm wavelength coverage, and preferably, described sensitive band spectrum is the spectrum of these two wave bands of 708nm and 1432nm.
The Nonlinear Prediction Models of Longjing tea moisture and characteristic spectrum reflectivity fried by described machine, be specially: the reflectivity utilizing sensitive band spectrum, use inversed-Gaussian model fit-spectra curve, ask for Red-edge parameter and absorb the degree of depth (area) two characteristic parameters, adopt small sample non-statistical theory and independent component analysis method, the Nonlinear Prediction Models obtained.
Described light source is infrarede emitting diode, comprise the first light source and secondary light source, in described step 1, the light sent by described first light source is divided into described first via light and the second road light after the first optical filter filtering, and the light sent by described secondary light source is divided into described first via light and the second road light after the second optical filter filtering.
Above specific embodiments of the invention are described.It is to be appreciated that the present invention is not limited to above-mentioned particular implementation, those skilled in the art can make various distortion or amendment within the scope of the claims, and this does not affect flesh and blood of the present invention.
Claims (6)
1. a Longjing tea moisture on-line measuring device fried by machine, it is characterized in that, comprises light source, spectroscope, photodetector, filtering and amplifying circuit, A/D convertor circuit, single-chip microcomputer, display, wherein:
The light that described light source sends is divided into first via light and the second road light by described spectroscope, and wherein, described first via light is reference light source, and described second road light is irradiate the incident light to Tea Samples;
Described photodetector is used for the spectral signal generating described reference light source according to the described reference light source collected, and generates the spectral signal of described reflected light according to the reflected light of the described incident light irradiation Tea Samples acquisition collected;
Described A/D convertor circuit is used for converting the spectral signal of the described reference light source after described filtering and amplifying circuit process to reference light source spectral digital signal, converts the spectral signal of the described reflected light after described filtering and amplifying circuit process to reflected light spectral digital signal;
Described single-chip microcomputer is used for according to described reference light source spectral digital signal and reflected light spectral digital signal, draw the reflectivity of sensitive band spectrum, the Nonlinear Prediction Models then reflectivity of described sensitive band spectrum being substituted into machine stir-fry Longjing tea moisture and characteristic spectrum reflectivity draws the moisture of tealeaves;
Described display is for showing the moisture of described tealeaves;
The Nonlinear Prediction Models of Longjing tea moisture and characteristic spectrum reflectivity fried by described machine, be specially: the reflectivity utilizing sensitive band spectrum, use inversed-Gaussian model fit-spectra curve, ask for Red-edge parameter and absorb the degree of depth two characteristic parameters, adopt small sample non-statistical theory and independent component analysis method, the Nonlinear Prediction Models obtained.
2. Longjing tea moisture on-line measuring device fried by machine according to claim 1, it is characterized in that, also comprise the first optical filter and the second optical filter, wherein, described light source comprises the first light source, secondary light source, the light that described first light source sends arrives described spectroscope through described first optical filter, and the light that described secondary light source sends arrives described spectroscope through described second optical filter.
3. Longjing tea moisture on-line measuring device fried by machine according to claim 1, and it is characterized in that, described sensitive band spectrum is the spectrum of 350-2500nm wavelength coverage.
4. Longjing tea moisture on-line measuring device fried by machine according to claim 3, and it is characterized in that, described sensitive band spectrum is the spectrum of these two wave bands of 708nm and 1432nm.
5. Longjing tea moisture on-line measuring device fried by machine according to claim 3, and it is characterized in that, described light source is infrarede emitting diode.
6. Longjing tea moisture on-line measuring device fried by machine according to claim 1, and it is characterized in that, the light that light source sends by described spectroscope is divided into first via light and the second road light according to the ratio of 1:1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210571483.1A CN103063603B (en) | 2012-12-25 | 2012-12-25 | Machine-fried Longjing tea moisture content on-line detection device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210571483.1A CN103063603B (en) | 2012-12-25 | 2012-12-25 | Machine-fried Longjing tea moisture content on-line detection device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103063603A CN103063603A (en) | 2013-04-24 |
| CN103063603B true CN103063603B (en) | 2015-04-29 |
Family
ID=48106316
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210571483.1A Expired - Fee Related CN103063603B (en) | 2012-12-25 | 2012-12-25 | Machine-fried Longjing tea moisture content on-line detection device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103063603B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103344575B (en) * | 2013-07-01 | 2015-11-25 | 江南大学 | Based on the many quality damage-free detection methods of dry green soy bean of hyper-spectral image technique |
| CN103528958A (en) * | 2013-10-24 | 2014-01-22 | 福建农林大学 | Device and realization method for rapidly detecting moisture content of tea leaves on line |
| CN107328901A (en) * | 2017-09-02 | 2017-11-07 | 刘芳 | A kind of crops leaf water content rapid detector |
| CN110174354B (en) * | 2019-06-24 | 2021-09-03 | 刘宗梅 | Spectral characteristic parameter-based detection device for moisture content of machine-fried homogenized tippy tea |
| CN113172993A (en) * | 2021-04-27 | 2021-07-27 | 广州诚鼎机器人有限公司 | Slurry humidity monitoring equipment and elliptical printing machine |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001116689A (en) * | 1999-10-15 | 2001-04-27 | Japan Science & Technology Corp | Moisture value estimating method of coal |
| DE19963561A1 (en) * | 1999-12-23 | 2001-07-05 | Merck Patent Gmbh | Method and device for online analysis of solvent mixtures |
| CN100460859C (en) * | 2006-04-29 | 2009-02-11 | 华东师范大学 | Sensing fiber infrared water determiner |
| CN101424636A (en) * | 2008-12-04 | 2009-05-06 | 中国计量学院 | A kind of device and method of rapidly and nondestructively detecting content of green tea composition |
| CN101949825B (en) * | 2010-08-17 | 2012-07-18 | 中国农业大学 | Leaf water near infrared non-destructive testing device and method in light open environment |
-
2012
- 2012-12-25 CN CN201210571483.1A patent/CN103063603B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN103063603A (en) | 2013-04-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103048278B (en) | Longjing tea moisture online test method fried by machine | |
| Köhler et al. | Assessing the potential of sun-induced fluorescence and the canopy scattering coefficient to track large-scale vegetation dynamics in Amazon forests | |
| Liu et al. | Evaluating the utility of solar-induced chlorophyll fluorescence for drought monitoring by comparison with NDVI derived from wheat canopy | |
| CN103063603B (en) | Machine-fried Longjing tea moisture content on-line detection device | |
| Steele et al. | A comparison of two techniques for nondestructive measurement of chlorophyll content in grapevine leaves | |
| CN101382488B (en) | Method for detecting nitrogen content in fresh tea by visible light-near infrared diffuse reflection spectrum technology | |
| Browne et al. | Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy | |
| CN103278473B (en) | The mensuration of pipering and moisture and method for evaluating quality in white pepper | |
| Steele et al. | Nondestructive estimation of leaf chlorophyll content in grapes | |
| CN101403689A (en) | Nondestructive detection method for physiological index of plant leaf | |
| CN110118742A (en) | Land table Vegetation canopy ecology water content remote sensing inversion method based on spectrum analysis | |
| CN105181606B (en) | The method that cane sugar content is distributed in peanut is detected based on high light spectrum image-forming technology | |
| Darvishsefat et al. | Evaluation of spectral reflectance of seven Iranian rice varieties canopies | |
| Nakaji et al. | Estimation of six leaf traits of East Asian forest tree species by leaf spectroscopy and partial least square regression | |
| CN108732137B (en) | Model and method for estimating plant species diversity based on hyperspectral remote sensing data | |
| CN105334166A (en) | Dual-detector near-infrared spectroscopy used for food composition analysis | |
| Endo et al. | Estimation of net photosynthetic rate based on in-situ hyperspectral data | |
| Tagesson et al. | Deriving seasonal dynamics in ecosystem properties of semi-arid savanna grasslands from in situ-based hyperspectral reflectance | |
| Zhang et al. | A highly chlorophyll-sensitive and LAI-insensitive index based on the red-edge band: CSI | |
| CN112858187A (en) | System and method for measuring anthocyanin of eggplant based on spectrum technology | |
| CN105115909B (en) | The method that fat content profiles in peanut are detected based on high light spectrum image-forming technology | |
| Viera Silva et al. | Calibration of a multi-species model for chlorophyll estimation in seedlings of Neotropical tree species using hand-held leaf absorbance meters and spectral reflectance | |
| CN211263179U (en) | Near-infrared detector for nondestructive identification of ginseng powder under forest | |
| Walsh et al. | Monitoring postharvest attributes: Instrumental techniques for measuring harvest maturity/fruit quality | |
| CN214121987U (en) | Eggplant anthocyanin measuring system based on spectrum technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20150429 Termination date: 20181225 |